Alzheimer?s disease (AD) is a neurodegenerative disorder characterized by dysfunction and deterioration of neurons resulting in loss of memory and progressive cognitive decline. We are using induced pluripotent stem cell (iPSC) technology coupled to comprehensive studies of patient populations to interrogate the cellular and molecular mechanisms underlying AD in an effort to better predict who will develop disease. Sporadic, late- onset AD (LOAD) patients all have high levels of A? plaques and tau tangles. However, A? plaque pathology does not correlate well with cognitive decline, and some people have high amyloid burden with intact cognition. The molecular mechanism underlying this protection has remained a mystery. We hypothesize that the cell and molecular mechanisms underlying protection from amyloid is in part intrinsically encoded within the cells of the brain. Here, we propose to study hiPSC lines from subsets of subjects who are deceased, who were deeply phenotyped clinically, pathologically, and genetically (the ROS and MAP cohorts of RUSH). We propose to begin interrogating these lines by focusing upon three subsets that lie on the extreme ends of the pathological spectrum: 1) no pathology, not cognitively impaired; NP-NCI: low A? levels, low tau tangle load and excellent cognition, 2) high pathology not cognitively impaired; ?HP-NCI?: high A? levels and excellent cognition, and 3) high pathology - Alzheimer?s disease, ?HP-AD?: high A? levels, high tau tangle load and impaired cognition. From neurons, astrocytes, and microglia derived from these iPSCs, we will perform whole transcriptome analyses using RNAseq, and integrate this information with RNAseq data acquired from brain tissue from ROS and MAP cohorts to determine if meaningful comparisons can be made at the gene and/or module level. If successful, this would lay the foundation for future studies aimed at predicting amyloid burden, and protection or vulnerability to amyloid. Importantly, we will interrogate the RNAseq data to examine if and how GWAS AD- risk SNPs affect expression of the genes in close proximity to the SNP in each of the three proposed cell types. Through these studies, we aim to determine the feasibility of using iPSC-derived cells to 1) predict transcriptomic signatures in the brain, and 2) study the effects of AD-associated SNPs on gene expression in the cell types most relevant to disease.